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How does predict.loess work?
3 messages · Recher She, David Winsemius, Greg Snow
On Apr 3, 2012, at 4:12 PM, Recher She wrote:
Dear R community, I am trying to understand how the predict function, specifically, the predict.loess function works. I understand that the loess function calculates regression parameters at each data point in 'data'. lo <- loess ( y~x, data)
Well, it produces a fitted-value at each point. Whether there are parameters at each point might depend on the degree of the fit.
p <- predict (lo, newdata) I understand that the predict function predicts values for 'newdata' according to the loess regression parameters. How does predict.loess do this in the case that 'newdata' is different from the original data x? How does the interpolation take place?
Type this at your console: getAnywhere(predict.loess) And after seeing that an additional functions is called type this: getAnywhere(predLoess) And then you will see that you have descended into a C function called 'C_loess_dfitse'.
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David Winsemius, MD West Hartford, CT
1 day later
Run the examples for the "loess.demo" function in the TeachingDemos package to get a better understanding of what goes into the loess predictions.
On Tue, Apr 3, 2012 at 2:12 PM, Recher She <rrrecher.she at gmail.com> wrote:
Dear R community, I am trying to understand how the predict function, specifically, the predict.loess function works. I understand that the loess function calculates regression parameters at each data point in 'data'. lo <- loess ( y~x, data) p <- predict (lo, newdata) I understand that the predict function predicts values for 'newdata' according to the loess regression parameters. How does predict.loess do this in the case that 'newdata' is different from the original data x? How does the interpolation take place? Thank you. ? ? ? ?[[alternative HTML version deleted]]
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Gregory (Greg) L. Snow Ph.D. 538280 at gmail.com